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LiveDataLink

by io.github.blackboxfoundry

entity_resolve

Read-onlyIdempotent

Resolve a company across US government sources in one call. Searches SEC EDGAR, EPA ECHO, and the sanctions lists by name and returns the candidate match and strong identifiers (SEC CIK, ticker, EPA registry id) found in each. Use this to confirm WHO an entity is and gather its IDs before pulling detail. Matches are name-based candidates to verify, not certain identity links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesCompany / organization name, e.g. 'Chevron Corporation', 'Acme Trucking LLC'.
stateNoOptional 2-letter US state to disambiguate location-based sources (e.g. 'TX').

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds valuable behavioral nuance by explicitly warning that matches are name-based candidates to verify, not certain identity links, and by disclosing that the tool consolidates multiple sources in one call. No contradiction with annotations exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, with every sentence earning its place: the core action, the specific data sources, the use case, and the critical caveat about candidate matches. There is no filler or redundant restatement of schema fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read-only tool with no output schema, the description provides enough context to understand what will be returned (candidate match and strong identifiers from each source). It is slightly incomplete because it does not address the relationship to the similarly named sibling 'resolve_entity', nor what happens when no match is found.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already documents both parameters thoroughly (100% coverage), including the optional state disambiguation. The description reinforces that searches are by name and that state helps with location-based sources, but it does not add substantial new meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: resolving a company across US government sources (SEC EDGAR, EPA ECHO, sanctions lists) and returning identifiers. It is specific about verb, resource, and scope, but it does not explicitly differentiate from the sibling tool 'resolve_entity', which could confuse an agent deciding between the two.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives practical guidance: use this to confirm an entity's identity and gather its IDs before pulling detail. This establishes clear context for when to invoke the tool, though it does not mention any exclusions or name alternative tools to consider instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.

Naming Consistency3/5

Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.

Tool Count1/5

294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.

Completeness4/5

The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.

Resources